GTM automation systems I run in production, AI agents I built for myself, and open-source tools anyone can use. Everything here exists and runs — nothing is a mock-up.
Seven repos of GTM automations plus Trigger.dev jobs, all pulled into one day-timeline: upcoming, ran, failed, never started. One-click re-run. A copy-context-for-debugging button. And an n8n watchdog that auto-dispatches any run GitHub Actions silently drops — the failure mode nobody notices until the data is stale. Built in one Claude Code session, live on Railway.
Related post: One of our “daily” GTM workflows was silently skipped 11 times in 30 days →A personal agent connected by webhooks. Every day it surfaces 5 random items from a 500–600-item GTM learning hub into Slack, receives captures from a Chrome extension into Notion, and translates my morning brief into a new voice via Sarvam.
Related post: The most underrated tool in my AI workflow right now is not Claude Code, Codex, or any agent — it is Webhooks →Captures each day’s Claude Code sessions, Granola meeting notes, and Slack threads into markdown. A weekly GitHub Action synthesizes what shipped and what’s pending to Confluence and Slack; a Hermes coaching note flags drift and repeating patterns.
Related post: Do you recall what you were working on during the week of May 1, 2026? →The production layer at Everstage: account scoring refresh, engagement intent reports, BDR performance tracking, outreach gap detection, and intel & reply extraction — running as daily crons.
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